Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...
Surface pasting is a hierarchical modeling technique capable of adding local details to tensor product Bspline surfaces without incurring significant computational costs. In this...
We demonstrate a system built using probabilistic techniques that allows for remarkably accurate localization across our entire office building using nothing more than the built-...
Andreas Haeberlen, Eliot Flannery, Andrew M. Ladd,...